Unifying knowledge graph learning and recommendation: towards a better understanding of user preferences
Incorporating knowledge graph (KG) into recommender system is promising in improving the recommendation accuracy and explainability. However, existing methods largely assume that a KG is complete and simply transfer the ”knowledge” in KG at the shallow level of entity raw data or embeddings. This ma...
Saved in:
Main Authors: | CAO, Yixin, WANG, Xiang, HE, Xiangnan, HU, Zikun, CHUA, Tat-Seng |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2019
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7288 https://ink.library.smu.edu.sg/context/sis_research/article/8291/viewcontent/3308558.3313705.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preference
by: Yixin Cao, et al.
Published: (2020) -
KGAT: Knowledge graph attention network for recommendation
by: WANG, Xiang, et al.
Published: (2019) -
KGAT: Knowledge Graph Attention Network for Recommendation
by: Xiang Wang, et al.
Published: (2020) -
Reinforced negative sampling over knowledge graph for recommendation
by: WANG, Xiang, et al.
Published: (2020) -
Learning and Reasoning on Graph for Recommendation
by: Xiang Wang, et al.
Published: (2020)